A multiphysics model to predict periventricular white matter hyperintensity growth during healthy brain aging.

Andreia Caçoilo, Berkin Dortdivanlioglu, Henry Rusinek, Johannes Weickenmeier
Author Information
  1. Andreia Caçoilo: Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States of America.
  2. Berkin Dortdivanlioglu: Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, Austin, TX 78712, United States of America.
  3. Henry Rusinek: Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, United States of America.
  4. Johannes Weickenmeier: Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States of America.

Abstract

Periventricular white matter hyperintensities (WMH) are a common finding in medical images of the aging brain and are associated with white matter damage resulting from cerebral small vessel disease, white matter inflammation, and a degeneration of the lateral ventricular wall. Despite extensive work, the etiology of periventricular WMHs remains unclear. We pose that there is a strong coupling between age-related ventricular expansion and the degeneration of the ventricular wall which leads to a dysregulated fluid exchange across this brain-fluid barrier. Here, we present a multiphysics model that couples cerebral atrophy-driven ventricular wall loading with periventricular WMH formation and progression. We use patient data to create eight 2D finite element models and demonstrate the predictive capabilities of our damage model. Our simulations show that we accurately capture the spatiotemporal features of periventricular WMH growth. For one, we observe that damage appears first in both the anterior and posterior horns and then spreads into deeper white matter tissue. For the other, we note that it takes up to 12 years before periventricular WMHs first appear and derive an average annualized periventricular WMH damage growth rate of 15.2 ± 12.7 mm/year across our models. A sensitivity analysis demonstrated that our model parameters provide sufficient sensitivity to rationalize subject-specific differences with respect to onset time and damage growth. Moreover, we show that the septum pellucidum, a membrane that separates the left and right lateral ventricles, delays the onset of periventricular WMHs at first, but leads to a higher WMH load in the long-term.

Keywords

References

  1. Front Neurol. 2019 Jul 25;10:784 [PMID: 31404147]
  2. Nat Commun. 2017 Mar 20;8:14787 [PMID: 28317912]
  3. Alzheimers Dement (N Y). 2019 Apr 09;5:107-117 [PMID: 31011621]
  4. Stroke. 2013 Apr;44(4):1037-42 [PMID: 23429507]
  5. Neurobiol Aging. 2015 Apr;36(4):1653-1658 [PMID: 25659858]
  6. Psychopharmacol Bull. 1988;24(4):661-3 [PMID: 3249768]
  7. Neuroimage. 2004 May;22(1):144-54 [PMID: 15110004]
  8. J Biomech. 2011 Apr 7;44(6):1158-63 [PMID: 21329927]
  9. J Neurosci. 2010 Feb 17;30(7):2600-10 [PMID: 20164345]
  10. Eur J Neurosci. 2021 Jun;53(12):3851-3878 [PMID: 32356339]
  11. AJR Am J Roentgenol. 1986 Aug;147(2):331-7 [PMID: 3487952]
  12. J Mech Behav Biomed Mater. 2023 Jul;143:105921 [PMID: 37269602]
  13. Neuroimage. 2006 Sep;32(3):1060-9 [PMID: 16839779]
  14. Am J Geriatr Psychiatry. 2006 Oct;14(10):842-9 [PMID: 17001024]
  15. Neural Regen Res. 2014 May 1;9(9):986-9 [PMID: 25206922]
  16. Tissue Barriers. 2014 Mar 19;2:e28426 [PMID: 25045600]
  17. Stroke. 2014 Jun;45(6):1721-6 [PMID: 24781079]
  18. Brain Pathol. 2015 Jan;25(1):35-43 [PMID: 25521175]
  19. Front Aging Neurosci. 2018 Nov 28;10:393 [PMID: 30546304]
  20. Arch Neurol. 2008 Sep;65(9):1202-8 [PMID: 18779424]
  21. Neurobiol Aging. 2016 Jun;42:116-23 [PMID: 27143428]
  22. Sci Rep. 2021 Nov 9;11(1):21956 [PMID: 34753951]
  23. Stroke. 2005 Nov;36(11):2342-3; author reply 2343-4 [PMID: 16239634]
  24. AJR Am J Roentgenol. 1987 Aug;149(2):351-6 [PMID: 3496763]
  25. Cereb Cortex. 2006 Nov;16(11):1584-94 [PMID: 16400155]
  26. Aging Cell. 2014 Apr;13(2):340-50 [PMID: 24341850]
  27. Neuroimage Clin. 2022;34:103019 [PMID: 35490587]
  28. J Mech Behav Biomed Mater. 2015 Jun;46:318-30 [PMID: 25819199]
  29. Ageing Res Rev. 2016 Sep;30:25-48 [PMID: 26827786]
  30. Brain Commun. 2019;1(1):fcz041 [PMID: 31894208]
  31. J Mech Behav Biomed Mater. 2010 Feb;3(2):158-66 [PMID: 20129415]
  32. Neurology. 2022 Nov 29;99(22):e2454-e2463 [PMID: 36123130]
  33. Eng Comput. 2022 Oct;38(5):3939-3955 [PMID: 37485473]
  34. J Neurol Neurosurg Psychiatry. 2001 Jan;70(1):9-14 [PMID: 11118240]
  35. Acad Radiol. 2021 Dec;28(12):1699-1708 [PMID: 33127308]
  36. Stroke. 2020 Jul;51(7):2111-2121 [PMID: 32517579]
  37. Alzheimers Res Ther. 2020 Oct 8;12(1):127 [PMID: 33032654]
  38. Stroke. 2005 Jan;36(1):50-5 [PMID: 15576652]
  39. J Alzheimers Dis. 2018;63(4):1347-1360 [PMID: 29843242]
  40. Neuroimage. 2018 Apr 15;170:174-181 [PMID: 28315460]
  41. Acta Neuropathol. 2011 Aug;122(2):171-85 [PMID: 21706175]
  42. Neuropsychol Rev. 2014 Sep;24(3):271-89 [PMID: 25146995]
  43. Acta Neuropathol. 2012 Oct;124(4):531-46 [PMID: 22576081]
  44. Neurology. 2007 Jan 16;68(3):214-22 [PMID: 17224576]
  45. Sci Rep. 2019 Mar 8;9(1):3998 [PMID: 30850617]
  46. Neuroimage Clin. 2022;35:103096 [PMID: 35764028]
  47. Arch Neurol. 1970 May;22(5):397-407 [PMID: 4985155]
  48. Brain Commun. 2022 Nov 04;4(6):fcac288 [PMID: 36415662]
  49. J Am Geriatr Soc. 1992 Sep;40(9):922-35 [PMID: 1512391]
  50. Mech Ageing Dev. 2021 Dec;200:111575 [PMID: 34600936]
  51. Acta Biomater. 2016 Sep 15;42:265-272 [PMID: 27475531]
  52. J Am Heart Assoc. 2015 Jun 23;4(6):001140 [PMID: 26104658]
  53. Neurobiol Aging. 2015 Feb;36(2):909-18 [PMID: 25457555]
  54. Neurology. 2004 Nov 9;63(9):1699-701 [PMID: 15534259]
  55. Front Mech Eng. 2021 Jul;7: [PMID: 35465618]
  56. Arch Neurol. 2003 Jul;60(7):989-94 [PMID: 12873856]

Grants

  1. P30 AG066512/NIA NIH HHS
  2. R21 AG067442/NIA NIH HHS
  3. U24 EB028980/NIBIB NIH HHS

Word Cloud

Created with Highcharts 10.0.0periventricularwhitematterdamageWMHmodelventricularwallgrowthWMHsfirstPeriventricularhyperintensitiesagingbraincerebraldegenerationlateralleadsacrossmultiphysicsloadingelementmodelsshow12sensitivityonsetcommonfindingmedicalimagesassociatedresultingsmallvesseldiseaseinflammationDespiteextensiveworketiologyremainsunclearposestrongcouplingage-relatedexpansiondysregulatedfluidexchangebrain-fluidbarrierpresentcouplesatrophy-drivenformationprogressionusepatientdatacreateeight2Dfinitedemonstratepredictivecapabilitiessimulationsaccuratelycapturespatiotemporalfeaturesoneobserveappearsanteriorposteriorhornsspreadsdeepertissuenotetakesyearsappearderiveaverageannualizedrate152±7mm/yearanalysisdemonstratedparametersprovidesufficientrationalizesubject-specificdifferencesrespecttimeMoreoverseptumpellucidummembraneseparatesleftrightventriclesdelayshigherloadlong-termpredicthyperintensityhealthyFinitemodelingMultiphysicsVentricular

Similar Articles

Cited By